• Journal of Nutrition and Health
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• v.41 no.8
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• pp.851-859
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• 2008

To promote the adoption of healthier eating patterns, this study was aimed to develop and evaluate alternative front of pack nutrition signposting concepts. Based on previous research, we developed two signposting concepts, Multiple Traffic Light (MTL) and Multiple Traffic Light with % Daily Value (MTL-%DV). The signposts featured three key nutrients, total sugar, saturated fat, and sodium. Actual food packaging with no front of pack signposting (NoSP) was included in the evaluation to act as a benchmark against which to compare the performance of the different signposting options. Using an interviewer administered method, we assessed the degree of understanding and time to interpret on a total of 534 subjects (194 elementary, 108 middle, and 103 high schoolers, 128 adults). In the individual product evaluations, MTL (87.0%) obtained the highest level of correct responses, followed by MTL-%DV (83.1%) and NoSP (52.2%). Except for signposting concepts, age, gender and living area were not associated with the degree of correct responses in multivariate analyses. When used to compare products with different colors of nutrient contents, correct responses were more than 90% for MTL-%DV (91.5%) and MTL (90.3%). The middle and high schoolers revealed the lower likelihood of correct response compared to the other two groups. In case of comparing products with same colors of nutrient contents, the proportion of correct responses was the highest in NoSP (90%), followed by MTL%DV (77.4%) and MTL (48.5%). In terms of time to interpret, MTL-%DV and MTL performed better than NoSP in the individual product evaluation and the comparison of two products with different colors of nutrient contents. NoSP performed the best in the comparison of two products with same colors of nutrient contents. A majority of the participants preferred MTL-%DV (78%) most and thought it the most useful in helping them make healthier food choices. Based on these findings, MTL-%DV was considered to most closely meet the objectives of the initiatives.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.43-56
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• 2020

Recommender systems help users make the best choice among various options. Especially, recommender systems play important roles in internet sites as digital information is generated innumerable every second. Many studies on recommender systems have focused on an accurate recommendation. However, there are some problems to overcome in order for the recommendation system to be commercially successful. First, there is a lack of transparency in the recommender system. That is, users cannot know why products are recommended. Second, the recommender system cannot immediately reflect changes in user preferences. That is, although the preference of the user's product changes over time, the recommender system must rebuild the model to reflect the user's preference. Therefore, in this study, we proposed a recommendation methodology using topic modeling and sequential association rule mining to solve these problems from review data. Product reviews provide useful information for recommendations because product reviews include not only rating of the product but also various contents such as user experiences and emotional state. So, reviews imply user preference for the product. So, topic modeling is useful for explaining why items are recommended to users. In addition, sequential association rule mining is useful for identifying changes in user preferences. The proposed methodology is largely divided into two phases. The first phase is to create user profile based on topic modeling. After extracting topics from user reviews on products, user profile on topics is created. The second phase is to recommend products using sequential rules that appear in buying behaviors of users as time passes. The buying behaviors are derived from a change in the topic of each user. A collaborative filtering-based recommendation system was developed as a benchmark system, and we compared the performance of the proposed methodology with that of the collaborative filtering-based recommendation system using Amazon's review dataset. As evaluation metrics, accuracy, recall, precision, and F1 were used. For topic modeling, collapsed Gibbs sampling was conducted. And we extracted 15 topics. Looking at the main topics, topic 1, top 3, topic 4, topic 7, topic 9, topic 13, topic 14 are related to "comedy shows", "high-teen drama series", "crime investigation drama", "horror theme", "British drama", "medical drama", "science fiction drama", respectively. As a result of comparative analysis, the proposed methodology outperformed the collaborative filtering-based recommendation system. From the results, we found that the time just prior to the recommendation was very important for inferring changes in user preference. Therefore, the proposed methodology not only can secure the transparency of the recommender system but also can reflect the user's preferences that change over time. However, the proposed methodology has some limitations. The proposed methodology cannot recommend product elaborately if the number of products included in the topic is large. In addition, the number of sequential patterns is small because the number of topics is too small. Therefore, future research needs to consider these limitations.

• Journal of Korean Society of Steel Construction
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• v.23 no.4
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• pp.417-428
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• 2011

Depending on the plastic deformation capacity required, structural steel design under the current codes can be classified into three categories: elastic, plastic, and seismic design. Most of the current steel codes explicitly forbid the use of a steel material with a yield strength higher than 450 MPa in the plastic design because of the concerns about its low plastic deformation capacity as well as the lack of test data on local and lateral torsional buckling behavior. In this study, flexural tests on full-scale H-shape members built with SM490A (ordinary steel or benchmark material) and HSB800 (high-strength steel) were carried out. The primary objective was to investigate the appropriateness of extrapolating the local buckling criterion of the current codes, which was originally developed for normal-strength steel, to the case of high-strength steel. All the SM490A specimens performed consistently with the current code criteria and exhibited sufficient strength and ductility. The performance of the HSB800 specimens was also very satisfactory from the strength perspective; even the specimens with a noncompact and slender flange developed the plastic moment capacity. The HSB800 specimens, however, showed an inferior plastic rotation capacity due to the premature tensile fracture of the beam bottom flange beneath the vertical stiffener at the loading point. The plastic rotation capacity that was achieved was less than 3 (or the minimum level required for a plastic design). Although the test results in this study indicate that the extrapolation of the current flange local-buckling criterion to the case of high-strength steel is conservative from the elastic design perspective, further testing together with an associated analytical study is required to identify the causes of the tensile fracture and to establish a flange slenderness criterion that is more appropriate for high-strength steel.

• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.57-71
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• 2013

Over a billion people in the world generate new news minute by minute. People forecasts some news but most news are from unexpected events such as natural disasters, accidents, crimes. People spend much time to watch a huge amount of news delivered from many media because they want to understand what is happening now, to predict what might happen in the near future, and to share and discuss on the news. People make better daily decisions through watching and obtaining useful information from news they saw. However, it is difficult that people choose news suitable to them and obtain useful information from the news because there are so many news media such as portal sites, broadcasters, and most news articles consist of gossipy news and breaking news. User interest changes over time and many people have no interest in outdated news. From this fact, applying users' recent interest to personalized news service is also required in news service. It means that personalized news service should dynamically manage user profiles. In this paper, a content-based news recommendation system is proposed to provide the personalized news service. For a personalized service, user's personal information is requisitely required. Social network service is used to extract user information for personalization service. The proposed system constructs dynamic user profile based on recent user information of Facebook, which is one of social network services. User information contains personal information, recent articles, and Facebook Page information. Facebook Pages are used for businesses, organizations and brands to share their contents and connect with people. Facebook users can add Facebook Page to specify their interest in the Page. The proposed system uses this Page information to create user profile, and to match user preferences to news topics. However, some Pages are not directly matched to news topic because Page deals with individual objects and do not provide topic information suitable to news. Freebase, which is a large collaborative database of well-known people, places, things, is used to match Page to news topic by using hierarchy information of its objects. By using recent Page information and articles of Facebook users, the proposed systems can own dynamic user profile. The generated user profile is used to measure user preferences on news. To generate news profile, news category predefined by news media is used and keywords of news articles are extracted after analysis of news contents including title, category, and scripts. TF-IDF technique, which reflects how important a word is to a document in a corpus, is used to identify keywords of each news article. For user profile and news profile, same format is used to efficiently measure similarity between user preferences and news. The proposed system calculates all similarity values between user profiles and news profiles. Existing methods of similarity calculation in vector space model do not cover synonym, hypernym and hyponym because they only handle given words in vector space model. The proposed system applies WordNet to similarity calculation to overcome the limitation. Top-N news articles, which have high similarity value for a target user, are recommended to the user. To evaluate the proposed news recommendation system, user profiles are generated using Facebook account with participants consent, and we implement a Web crawler to extract news information from PBS, which is non-profit public broadcasting television network in the United States, and construct news profiles. We compare the performance of the proposed method with that of benchmark algorithms. One is a traditional method based on TF-IDF. Another is 6Sub-Vectors method that divides the points to get keywords into six parts. Experimental results demonstrate that the proposed system provide useful news to users by applying user's social network information and WordNet functions, in terms of prediction error of recommended news.

• Radiation Oncology Journal
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• v.25 no.2
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• pp.79-92
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• 2007

[ $\underline{Purpose}$ ]: For the first time, a nationwide survey in the Republic of Korea was conducted to determine the basic parameters for the treatment of esophageal cancer and to offer a solid cooperative system for the Korean Pattern of Care Study database. $\underline{Materials\;and\;Methods}$: During $1998{\sim}1999$, biopsy-confirmed 246 esophageal cancer patients that received radiotherapy were enrolled from 23 different institutions in South Korea. Random sampling was based on power allocation method. Patient parameters and specific information regarding tumor characteristics and treatment methods were collected and registered through the web based PCS system. The data was analyzed by the use of the Chi-squared test. $\underline{Results}$: The median age of the collected patients was 62 years. The male to female ratio was about 91 to 9 with an absolute male predominance. The performance status ranged from ECOG 0 to 1 in 82.5% of the patients. Diagnostic procedures included an esophagogram (228 patients, 92.7%), endoscopy (226 patients, 91.9%), and a chest CT scan (238 patients, 96.7%). Squamous cell carcinoma was diagnosed in 96.3% of the patients; mid-thoracic esophageal cancer was most prevalent (110 patients, 44.7%) and 135 patients presented with clinical stage III disease. Fifty seven patients received radiotherapy alone and 37 patients received surgery with adjuvant postoperative radiotherapy. Half of the patients (123 patients) received chemotherapy together with RT and 70 patients (56.9%) received it as concurrent chemoradiotherapy. The most frequently used chemotherapeutic agent was a combination of cisplatin and 5-FU. Most patients received radiotherapy either with 6 MV (116 patients, 47.2%) or with 10 MV photons (87 patients, 35.4%). Radiotherapy was delivered through a conventional AP-PA field for 206 patients (83.7%) without using a CT plan and the median delivered dose was 3,600 cGy. The median total dose of postoperative radiotherapy was 5,040 cGy while for the non-operative patients the median total dose was 5,970 cGy. Thirty-four patients received intraluminal brachytherapy with high dose rate Iridium-192. Brachytherapy was delivered with a median dose of 300 cGy in each fraction and was typically delivered $3{\sim}4\;times$. The most frequently encountered complication during the radiotherapy treatment was esophagitis in 155 patients (63.0%). $\underline{Conclusion}$: For the evaluation and treatment of esophageal cancer patients at radiation facilities in Korea, this study will provide guidelines and benchmark data for the solid cooperative systems of the Korean PCS. Although some differences were noted between institutions, there was no major difference in the treatment modalities and RT techniques.